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基于NDVI与丰度关系的MODIS影像浒苔混合像元分解方法

丁一 黄娟 崔廷伟 万振文 张怡 曹丛华 陈超 肖艳芳

丁一, 黄娟, 崔廷伟, 万振文, 张怡, 曹丛华, 陈超, 肖艳芳. 基于NDVI与丰度关系的MODIS影像浒苔混合像元分解方法[J]. 海洋学报, 2015, 37(7): 123-131.
引用本文: 丁一, 黄娟, 崔廷伟, 万振文, 张怡, 曹丛华, 陈超, 肖艳芳. 基于NDVI与丰度关系的MODIS影像浒苔混合像元分解方法[J]. 海洋学报, 2015, 37(7): 123-131.
Ding Yi, Huang Juan, Cui Tingwei, Wan Zhenwen, Zhang Yi, Cao Conghua, Chen Chao, Xiao Yanfang. The decomposition method of MODIS images Enteromorpha mixed pixels based on the relation of NDVI to abundance[J]. Haiyang Xuebao, 2015, 37(7): 123-131.
Citation: Ding Yi, Huang Juan, Cui Tingwei, Wan Zhenwen, Zhang Yi, Cao Conghua, Chen Chao, Xiao Yanfang. The decomposition method of MODIS images Enteromorpha mixed pixels based on the relation of NDVI to abundance[J]. Haiyang Xuebao, 2015, 37(7): 123-131.

基于NDVI与丰度关系的MODIS影像浒苔混合像元分解方法

基金项目: 国家海洋局青年海洋科学基金项目(2012405);海洋公益性行业科研专项经费项目(201205010,2013418025-2);国家海洋局第一海洋研究所基本科研业务费专项资金项目(GY0214T03).

The decomposition method of MODIS images Enteromorpha mixed pixels based on the relation of NDVI to abundance

  • 摘要: MODIS影像是浒苔业务化卫星遥感监测的重要数据源,但其空间分辨率(250 m)较低,混合像元效应导致传统的NDVI(Normalized Difference Vegetation Index)阈值法浒苔提取误差较大.为解决此问题,本文以准同步的较高分辨率的HJ-1 CCD影像浒苔提取结果为基准,建立基于MODIS NDVI与浒苔像元丰度(浒苔覆盖面积占像元面积百分比)关系的浒苔信息提取模型,利用该模型可提取每个像元的丰度(即浒苔覆盖率),从而提高整景影像浒苔覆盖面积提取精度.该模型可为浒苔灾害等级的确定以及防灾减灾应急决策提供支持.
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    http://modis.gsfc.nasa.gov/about/design.php
    http://www.cresda.com/n16/n1130/n1582/8384.html
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出版历程
  • 收稿日期:  2014-09-04
  • 修回日期:  2014-12-08

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